ABSTRACT. For 25 years, we have investigated the genetic bases of familial and sporadic Alzheimer?s disease (AD) among Caribbean Hispanics in the US and in the Dominican Republic, contributing samples and data to the Alzheimer?s Disease Genetics Consortium and the Alzheimer?s Disease Sequencing Project. In this new proposal, we intend to integrate the genetic analyses of AD in Caribbean Hispanics with deep molecular phenotyping: epigenomics, transcriptomics, proteomics and metabolomics from whole blood, plasma, cerebrospinal fluid and brain tissue where possible. Multi-omics data generated in this minority population will be used to understand the effects of gene variants on disease, clarify the affected proteins and pathways that underlie AD. Compared with non-Hispanics, we have shown that Caribbean Hispanics are three times more likely to develop AD by age 75 years. If they have family members with AD their risk is five times higher. From the study entitled, ?Estudio Familiar Investigar Genetica de Alzheimer? (EFIGA, RF1AG01543) we have clinical information and biological samples in 513 families multiply affected by AD, including 4,481 individuals of which 178 families (35%) have four or more affected relatives and 1,155 individuals with sporadic AD and 1,476 healthy controls that includes members of the Caribbean Hispanic Religious Orders. Our comprehensive genetic analyses in Caribbean Hispanics have yielded putative variants in ABCA7, BIN1, CD2AP, CLU, CR1, EPHA1, MS4A4A/MS4A6A, PICALM, SORL1, FBXL7 and SRCAP, each of which has been replicated. To covert these genetic findings into meaningful applications to AD we now want to focus our efforts on the relationships between the genetic variants and epigenomics, transcriptomics, proteomics and metabolomics. From the existing cohorts of genetically characterized individuals described above we will assemble a new multi-omics cohort. This multi-omics cohort of 1,000 individuals will identify systems-level alterations in AD and will provide insight into the mechanisms underlying genetic variants, assist in identifying disease pathways, putative protein- protein interactions and downstream metabolites that can be used to inform preclinical work, develop biomarkers and eventually therapeutic targets for drug discovery. The overarching goal is to use a genetic variant-centered integration of multiple omics layers to identify specific causal genes and investigate how they may perturb pathways leading to disease.